Data Integration is the process of combining two or more data sets together for sharing and analysis.
Data integration is important to network designers of both service providers and enterprise. Integration of data technologies has accelerated rapidly in recent years because of both supply- and demand-side interactions. Customers are leveraging investment in network infrastructure to take advantage of integrated applications such as voice applications. This may increase the productivity of users and differentiate services.
Data integration requires combining and matching information in different sources, and resolving a variety of conflict.
Data integration means working within your existing application environment to ensure that high quality information arrives at new data targets during data migration or consolidation efforts.
The availability of integrated data from multiple independent, heterogenous data sources is crucial for many applications.
One of the most important applications of data integration is the merging of legacy databases and infrastructure with current enterprise applications.
In order to minimize the risk to deliver the project on time and within budget, you need proper data integration techniques.
Data integration is not just about matching and linking data together. It’s also about gaining access to the right data sources at the right time. .